Exploration of differential expression and biological significance of amino acid metabolism genes in osteoarthritis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40726988", "kind": "science-record", "revision": 4, "content_hash": "sha256:b14783e60b7fed39d7b17aabed4afe208d63ff17705775d474673c77179c4ddb", "created_at": "2026-11-01T20:30:50Z", "updated_at": "2026-11-01T22:56:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of differential expression and biological significance of amino acid metabolism genes in osteoarthritis.", "doi": "10.3389/fimmu.2025.1588072", "pmid": "40726988", "authors": ["Zhenghuan Zhu", "Jiaqing Meng", "Junfeng Hu", "Lingmin Hu", "Wenge Ding", "Wanchao Zhang", "Chuang Zhao", "Lin Feng", "Kejie Wang"], "journal": "Frontiers in immunology", "year": 2025, "abstract": "Background: Osteoarthritis (OA) is a widespread disorder affecting joints, recognized for cartilage wear and inflammatory responses, which substantially affects patients' quality of life. This research aim to discover amino acid metabolism-related differentially expressed genes (AAMRDEGs) and clarify their functions in OA pathogenesis.\nMethods: Herein, we conducted an analysis of combined GEO datasets (GSE55457, GSE55235, and GSE12021), identifying 169 AAMRDEGs and indicating their importance in chondrocyte function and inflammation. Furthermore, significant correlations were observed between various immune cell types, underscoring the intricate function of the immune system in OA. Thereafter, we developed highly accurate diagnostic models using LASSO regression and SVM methodologies, achieving an area under the curve > 0.9. Protein-protein interaction analysis revealed significant interactions among MTHFD2, PPP1R15A, SLC2A4, and WNT5B, with their expression levels corroborated using single-cell datasets, highlighting the potential therapeutic targets. To confirm the presence of these hub AAMRGs, real-time polymerase chain reaction and immunohistochemistry were employed.\nResults: We identified 2,115 DEGs between OA and control groups, with 1,062 upregulated and 1,053 downregulated. Enrichment analysis linked AAMRDEGs to amino acid catabolism and multiple KEGG pathways, indicating their importance in chondrocyte function and inflammation. Furthermore, significant correlations were observed between various immune cell types, underscoring the intricate role of the immune system in OA. Subsequently, we developed highly accurate diagnostic models using LASSO regression and SVM methodologies, achieving an area under the curve > 0.9. Protein-protein interaction analysis revealed significant interactions among MTHFD2, PPP1R15A, SLC2A4, and WNT5B, with their expression levels corroborated using single-cell datasets, highlighting the potential therapeutic targets. Real-time polymerase chain reaction and immunohistochemistry were used to validate the expression of these hub amino acid metabolism-related genes.\nConclusion: This investigation presents a detailed evaluation of AAMRGs in OA, highlighting their roles in disease pathogenesis and offering new insights for therapeutic research. Key genes SLC2A4, MTHDF2, and WNT5B might function as markers for early identification and personalized OA treatment.", "claims": [{"id": "claim-method", "statement": "To mitigate overfitting, LASSO regression with a penalty term was performed using the glmnet package (24), incorporating a penalty term.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40726988", "locator": "sections[8] \"Construction of OA diagnostic model\" paragraph 2", "quote": "To mitigate overfitting, LASSO regression with a penalty term was performed using the glmnet package (24), incorporating a penalty term."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12021"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12021"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40726988", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2025.1588072", "sha256": "sha256:87704b1b96559252e6884b1af231b9adcd40d8cdfca33bec762de5d51ec9c679", "bytes": 71972, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2025.1588072", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12301216", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE12021", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12021", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE12021", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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